Similarities and Differences in Gene Expression Networks Between the Breast Cancer Cell Line Michigan Cancer Foundation-7 and Invasive Human Breast Cancer Tissues

dc.contributor.authorTran, Vy
dc.contributor.authorKim, Robert
dc.contributor.authorMaertens, Mikhail
dc.contributor.authorHartung, Thomas
dc.contributor.authorMaertens, Alexandra
dc.date.accessioned2021-06-15T09:13:04Z
dc.date.available2021-06-15T09:13:04Z
dc.date.issued2021eng
dc.description.abstractFailure to adequately characterize cell lines, and understand the differences between in vitro and in vivo biology, can have serious consequences on the translatability of in vitro scientific studies to human clinical trials. This project focuses on the Michigan Cancer Foundation-7 (MCF-7) cells, a human breast adenocarcinoma cell line that is commonly used for in vitro cancer research, with over 42,000 publications in PubMed. In this study, we explore the key similarities and differences in gene expression networks of MCF-7 cell lines compared to human breast cancer tissues. We used two MCF-7 data sets, one data set collected by ARCHS4 including 1032 samples and one data set from Gene Expression Omnibus GSE50705 with 88 estradiol-treated MCF-7 samples. The human breast invasive ductal carcinoma (BRCA) data set came from The Cancer Genome Atlas, including 1212 breast tissue samples. Weighted Gene Correlation Network Analysis (WGCNA) and functional annotations of the data showed that MCF-7 cells and human breast tissues have only minimal similarity in biological processes, although some fundamental functions, such as cell cycle, are conserved. Scaled connectivity-a network topology metric-also showed drastic differences in the behavior of genes between MCF-7 and BRCA data sets. Finally, we used canSAR to compute ligand-based druggability scores of genes in the data sets, and our results suggested that using MCF-7 to study breast cancer may lead to missing important gene targets. Our comparison of the networks of MCF-7 and human breast cancer highlights the nuances of using MCF-7 to study human breast cancer and can contribute to better experimental design and result interpretation of study involving this cell line.eng
dc.description.versionpublishedeng
dc.identifier.doi10.3389/frai.2021.674370eng
dc.identifier.pmid34056582eng
dc.identifier.ppn1767945841
dc.identifier.urihttps://kops.uni-konstanz.de/handle/123456789/53974
dc.language.isoengeng
dc.rightsAttribution 4.0 International
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/
dc.subjectWGCNA, TCGA, cell line relevance, network analysis, human breast cancer tissues, MCF-7eng
dc.subject.ddc570eng
dc.titleSimilarities and Differences in Gene Expression Networks Between the Breast Cancer Cell Line Michigan Cancer Foundation-7 and Invasive Human Breast Cancer Tissueseng
dc.typeJOURNAL_ARTICLEeng
dspace.entity.typePublication
kops.citation.bibtex
@article{Tran2021Simil-53974,
  year={2021},
  doi={10.3389/frai.2021.674370},
  title={Similarities and Differences in Gene Expression Networks Between the Breast Cancer Cell Line Michigan Cancer Foundation-7 and Invasive Human Breast Cancer Tissues},
  volume={4},
  journal={Frontiers in artificial intelligence},
  author={Tran, Vy and Kim, Robert and Maertens, Mikhail and Hartung, Thomas and Maertens, Alexandra},
  note={Article Number: 674370}
}
kops.citation.iso690TRAN, Vy, Robert KIM, Mikhail MAERTENS, Thomas HARTUNG, Alexandra MAERTENS, 2021. Similarities and Differences in Gene Expression Networks Between the Breast Cancer Cell Line Michigan Cancer Foundation-7 and Invasive Human Breast Cancer Tissues. In: Frontiers in artificial intelligence. Frontiers Research Foundation. 2021, 4, 674370. eISSN 2624-8212. Available under: doi: 10.3389/frai.2021.674370deu
kops.citation.iso690TRAN, Vy, Robert KIM, Mikhail MAERTENS, Thomas HARTUNG, Alexandra MAERTENS, 2021. Similarities and Differences in Gene Expression Networks Between the Breast Cancer Cell Line Michigan Cancer Foundation-7 and Invasive Human Breast Cancer Tissues. In: Frontiers in artificial intelligence. Frontiers Research Foundation. 2021, 4, 674370. eISSN 2624-8212. Available under: doi: 10.3389/frai.2021.674370eng
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kops.sourcefieldFrontiers in artificial intelligence. Frontiers Research Foundation. 2021, <b>4</b>, 674370. eISSN 2624-8212. Available under: doi: 10.3389/frai.2021.674370deu
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